Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms

Spatial heterogeneity of habitats and different foraging strategies can result in dissimilar patterns of habitat selection among individuals in a population. Studies have demonstrated that incorporating individual variation can influence model inferences. Thus, individual variation is increasingly b...

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Main Author: Ebinger, Michael Ryan
Other Authors: Chairperson, Graduate Committee: Robert A. Garrott
Format: Thesis
Language:English
Published: Montana State University - Bozeman, College of Letters & Science 2016
Subjects:
Online Access:https://scholarworks.montana.edu/xmlui/handle/1/14623
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record_format openpolar
spelling ftmontanastateu:oai:scholarworks.montana.edu:1/14623 2023-05-15T18:42:14+02:00 Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms Ebinger, Michael Ryan Chairperson, Graduate Committee: Robert A. Garrott Greater Yellowstone Ecosystem (Idaho, Mont., Wyo.) 2016 application/pdf https://scholarworks.montana.edu/xmlui/handle/1/14623 en eng Montana State University - Bozeman, College of Letters & Science https://scholarworks.montana.edu/xmlui/handle/1/14623 Copyright 2016 by Michael Ryan Ebinger Mathematical statistics Grizzly bear Habitat selection Ecology Whitebark pine Thesis 2016 ftmontanastateu 2022-06-06T07:28:41Z Spatial heterogeneity of habitats and different foraging strategies can result in dissimilar patterns of habitat selection among individuals in a population. Studies have demonstrated that incorporating individual variation can influence model inferences. Thus, individual variation is increasingly being incorporated in habitat selection studies. Our objective was to advance the concept of individual variation in habitat selection by incorporating varying shapes (i.e., function forms) of responses among individuals. We used simulation modeling to develop a new analytical framework and introduce a new habitat selection metric, the Normalized Selection Ratio (NSR). Our results demonstrated the ability of the NSR to correctly estimate the strength and shape of complex simulated patterns of habitat selection, while simultaneously protecting against over-fitting. Using a simulated population of individuals, we showed how our approach can scale-up individual responses to facilitate population-level inference. We demonstrated how hierarchical clustering of individual-level response curves can identify and quantitatively describe different types of habitat selection within a population. When applied in a temporally dynamic framework, we showed that the NSR can detect ecological dynamics in habitat selection with quantitatively different inferences from analyses that pool data over time. We illustrated application of our approach using global positioning system (GPS) telemetry data for grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). We investigated the direction (preference or avoidance) and shapes of grizzly bear selection for whitebark pine (Pinus albicaulis) habitat during fall from 2007 to 2014. Our general conclusions support previous findings that grizzly bears exhibit a high degree of individual variation in habitat selection. Our approach of hierarchically clustering response curves detected 4 groups of grizzly bears with distinctly different patterns of whitebark pine habitat selection. ... Thesis Ursus arctos Montana State University (MSU): ScholarWorks
institution Open Polar
collection Montana State University (MSU): ScholarWorks
op_collection_id ftmontanastateu
language English
topic Mathematical statistics
Grizzly bear
Habitat selection
Ecology
Whitebark pine
spellingShingle Mathematical statistics
Grizzly bear
Habitat selection
Ecology
Whitebark pine
Ebinger, Michael Ryan
Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
topic_facet Mathematical statistics
Grizzly bear
Habitat selection
Ecology
Whitebark pine
description Spatial heterogeneity of habitats and different foraging strategies can result in dissimilar patterns of habitat selection among individuals in a population. Studies have demonstrated that incorporating individual variation can influence model inferences. Thus, individual variation is increasingly being incorporated in habitat selection studies. Our objective was to advance the concept of individual variation in habitat selection by incorporating varying shapes (i.e., function forms) of responses among individuals. We used simulation modeling to develop a new analytical framework and introduce a new habitat selection metric, the Normalized Selection Ratio (NSR). Our results demonstrated the ability of the NSR to correctly estimate the strength and shape of complex simulated patterns of habitat selection, while simultaneously protecting against over-fitting. Using a simulated population of individuals, we showed how our approach can scale-up individual responses to facilitate population-level inference. We demonstrated how hierarchical clustering of individual-level response curves can identify and quantitatively describe different types of habitat selection within a population. When applied in a temporally dynamic framework, we showed that the NSR can detect ecological dynamics in habitat selection with quantitatively different inferences from analyses that pool data over time. We illustrated application of our approach using global positioning system (GPS) telemetry data for grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem (GYE). We investigated the direction (preference or avoidance) and shapes of grizzly bear selection for whitebark pine (Pinus albicaulis) habitat during fall from 2007 to 2014. Our general conclusions support previous findings that grizzly bears exhibit a high degree of individual variation in habitat selection. Our approach of hierarchically clustering response curves detected 4 groups of grizzly bears with distinctly different patterns of whitebark pine habitat selection. ...
author2 Chairperson, Graduate Committee: Robert A. Garrott
format Thesis
author Ebinger, Michael Ryan
author_facet Ebinger, Michael Ryan
author_sort Ebinger, Michael Ryan
title Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
title_short Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
title_full Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
title_fullStr Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
title_full_unstemmed Varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
title_sort varying nonlinear dependencies in habitat selection: estimating instead of imposing functional forms
publisher Montana State University - Bozeman, College of Letters & Science
publishDate 2016
url https://scholarworks.montana.edu/xmlui/handle/1/14623
op_coverage Greater Yellowstone Ecosystem (Idaho, Mont., Wyo.)
genre Ursus arctos
genre_facet Ursus arctos
op_relation https://scholarworks.montana.edu/xmlui/handle/1/14623
op_rights Copyright 2016 by Michael Ryan Ebinger
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